1. Field of the Invention
The field of the invention is data processing, or, more specifically, methods, apparatuses, and computer program products for utilizing a kernel administration hardware thread of a multi-threaded, multi-core compute node of a parallel computer.
2. Description of Related Art
The development of the EDVAC computer system of 1948 is often cited as the beginning of the computer era. Since that time, computer systems have evolved into extremely complicated devices. Today's computers are much more sophisticated than early systems such as the EDVAC. Computer systems typically include a combination of hardware and software components, application programs, operating systems, processors, buses, memory, input/output devices, and so on. As advances in semiconductor processing and computer architecture push the performance of the computer higher and higher, more sophisticated computer software has evolved to take advantage of the higher performance of the hardware, resulting in computer systems today that are much more powerful than just a few years ago.
Modern computing systems can be massively parallel and include many compute nodes within a computing system. Parallel computing is the partitioning or dividing of an algorithm into units, often called threads, which are simultaneously or concurrently executed on multiple processors. The intermediate results of these multiple threads are then combined into a final result. Thus, parallel computing is based on the idea that the process of solving a problem usually can be divided into smaller tasks, which may be carried out simultaneously with some coordination. Parallel computing is valuable because performing a large task by the parallel execution of smaller tasks can be faster than performing the large task via one serial (non-parallel) algorithm.
The parallel threads are often implemented on computer systems that include multiple processors and/or on multiple computer systems (often called compute nodes or simply nodes) that comprise processors, which run the parallel threads or local instances of global applications to accomplish tasks. The parallel thread or threads local to a particular node need a way to communicate with other parallel threads, which is often accomplished via a technique known as message passing. To ensure proper communication between various nodes, a standard known as the Message Passing Interface (MPI) has been developed.
Under the MPI standard, an MPI program consists of autonomous processes, executing their own code, which need not be identical. Typically, each process or application communicates via calls to MPI communication primitives, where each process executes in its own and shared memory. Such message passing allows the local processors comprising the node and applications running thereon (a thread or instance of the global application or process) to cooperate with each other. MPI is available on a wide variety of platforms, ranging from networks of workstations to massively parallel systems. Each message received by a compute node is eventually stored by the compute node. In a parallel computer with hundreds or thousands of compute nodes, where each compute node is continually storing thousands of messages, efficient storage of the messages plays an important role in the overall efficiency of the parallel computer.